Is Python a Legitimate Data Analysis Tool?

Back in May we discussed using Python, R, and Octave as data analysis tools, and compared the relative strength of each. One point of contention was whether Python could be considered a legitimate tool for such work. Now, Bei Lu writes while Python on its own may be lacking, Python with packages is very much up to the task: "My passion with Python started with its natural language processing capability when paired with the Natural Language Toolkit (NLTK). Considering the growing need for text mining to extract content themes and reader sentiments (just to name a few functions), I believe Python+packages will serve as more mainstream analytical tools beyond the academic arena." She also discusses an emerging set of solutions for R which let it better handle big data.

really?

[Anonymous Coward]

Any Turing-complete language is a legitimate data analysis tool.

Re:Call me old fashioned

[ceoyoyo]

It depends how complicated the math is.

I wrote a general linear model in Python because I was unhappy with the existing ones and I wanted an intimate knowledge of how it worked. I wrote most of a general linear mixed model, but then decided it wasn't worth the time and just used the one in R via RPy2. Then it turned out the one built into R was too slow, so I upgraded to the one in the lme R package. That exists because a lot of smart people use R.

But sure, if your "data analysis" involves multiplication and maybe a t-test or two, it doesn't really matter what you use.